Introduction

Statistical Examination of Challenge Test Data and Modelling

Vasco Cadavez

Polytechnic Institute of Bragança

Mountain Research Center

Ursula Gonzales-Barron

Polytechnic Institute of Bragança

Mountain Research Center

2024-04-30

Class summary

  • You will learn:
    • The goals of predictive microbiology
    • The models classification
    • The definition of challenge test
    • How to carry out a challenge test
    • How to check a data set from challenge tests using R software
    • How to fit a primary model using R software
    • How to fit a secondary model using R software
  • Materials needed:
    • This presentation
    • Two R scripts
      • Unit1-ChallengeTestsDataAnalysisPGM.R
      • Unit1-ChallengeTestsDataAnalysisSGM.R
    • The accompanying videos

Predictive microbiology

Predictive microbiology objectives

  • Aims the description of the responses of microorganism's to particular environmental conditions, such as:
    • Temperature
    • pH
    • Organic acids
    • Water activity
  • Based on mathematical models developed using data collected at laboratory level
  • Software is used to fit the models to experimental data in order to characterize the microbes responses

Models classification

Primary models

  • Describe the microbial behaviour as a function of time
    • Growth
    • Inactivation
    • Survival
  • Fit models to experimental data to estimate the kinetic parameters
    • \(\lambda\): lag phase duration
    • \(k\): Maximum growth rate, or
    • \(\mu\): Specific growth rate
    • \(M\): Maximum population density

Secondary models

  • Describe the kinetic parameters as a function of environmental conditions
    • Temperature
    • pH
    • Water activity

Tertiary models

  • Primary and secondary models are integrated in software tools
  • Used by
    • food safety assessors
    • R&D managers
    • Quality managers

Tertiary models

Examples: https://fsqanalytics.github.io/predmicror/

Tertiary models

Examples: https://www.uco.es/investiga/grupos/hibro/en/microhibro

Tertiary models

Examples: https://symprevius.eu/en/

Challenge tests

Objectives

  • Study the microbial growth potential

    • We assess whether or not the food favours the growth of microorganisms
    • Compromise the consumer health
    • Accelerate food spoilage

  • Processes validation by studying the degree of lethality against a target organism or group of target organisms.

  • Useful to determine the potential shelf life of foods.

  • The food industry use challenge tests to improve the safety and quality of its products.

How to carry out a challenge test?

  • Food is contaminated and analysed in the environmental conditions in which it is normally produced, distributed, stored and marketed

  • Inoculation should be carried out at the most critical stages of processing

  • We can't carry out these tests on production lines

  • So we need laboratorial experiments

How to carry out a challenge test?

Examples

How to carry out a challenge test?

Examples

How to carry out a challenge test?

Examples

References

Baranyi, J, PJ McClure, JP Sutherland, and TA Roberts. 1993. “Modeling Bacterial Growth Responses.” Journal of Industrial Microbiology 12 (3-5): 190–94.
Gonzales-Barron, Ursula, and Vasco Cadavez. 2019. Handbook of Predictive Microbiology Growth Models Using R. Edited by Ursula Gonzales-Barron and Vasco Cadavez. Bragança, Portugal: Bringráfica Indústrias Gráficas, LDA.
ISO20976-1:2019. 2019. Microbiology of the Food Chain Requirements and Guidelines for Conducting Challenge Tests of Food and Feed Products Part 1: Challenge Tests to Study Growth Potential, Lag Time and Maximum Growth Rate.
ISO20976-2:2019. 2019. Microbiology of the Food Chain Requirements and Guidelines for Conducting Challenge Tests of Food and Feed Products Part 2: Challenge Tests to Study Inactivation Potential and Kinetic Parameters.
McMeekin, T. A., J. Olley, T. Ross, and D. A. Ratkowsky. 1993. Predictive Microbiology: Theory and Application. Taunton, UK: Research Studies Press.
Whiting, R. C., and R. L. Buchanan. 1993. “A Classification of Models for Predictive Microbiology.” Food Microbiology 10: 175–77.
Zwietering, M. H., I. Jongenburger, F. M. Rombouts, and K. van’t Riet. 1990. “Modeling of the Bacterial Growth Curve.” Applied and Environmental Microbiology 56 (6): 1875–81.